Calculating ROI for Data Governance
Initiatives
By Harikrishna S. Aravapalli
Data governance is a set of processes, organization structures,
standards and technologies which are required to coordinate and
ensure the availability, accessibility, quality, consistency, auditability
and security of data in an organization. It provides a framework for the
IT and business to work together to establish confidence and credibility
in the enterprise’s information.
A good data governance initiative will ensure a seamless data flow
across the organization and can help to unlock the potential of the data
assets in an organization. Customers, vendors and the organization’s
employees feel confident about using the data for their individual
purposes. Some of the other benefits are greater awareness among
the data stakeholders, better data integration, better handling of
compliance issues and the ability to deliver data of the utmost quality.
While we may know the “what,” “when,” “where,” and “who” aspects of
data governance, senior executives connected with data governance
initiatives much also answer the question “how much?” The question
about how much involves creating a measure to quantify a data
governance initiative. Is there a way to compute upfront the “how
much” aspect of a data governance initiative?
Communicating Value
Just like other IT initiatives, data governance can also have a
mechanism to compute ROI. An ROI analysis will help in justifying the
need for a data governance initiative. Let’s take a look at how the ROI
for data governance is computed.
Conceptually, the ROI for data governance is the difference between
the savings from fixing data-related issues and the cost of
implementing a data governance initiative, towards the same.
Summary
Data quality and compliance issues necessitate the need for a data
governance initiative in an organization. But it can be very difficult to
justify to the business sponsors the funding of a data governance
project, as it is more of an enabler without any tangible outputs or
artifacts.
Hence, a method to quantify the need for a data governance initiative
by highlighting the ROI can be helpful. These quantifying methods can
also serve as thresholds for proactively monitoring the health check of
any data management program and also determining the right time to
launch a data governance initiative.
Harikrishna S. Aravapalli is a senior technical architect at SETLABS,
Infosys and has 13 years of experience in databases, data warehouses
and business intelligence technologies. Aravapalli worked for Wipro
and Accenture prior to Infosys. He may be reached at
harikrishna_sa@infosys.com.
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The following sequence of steps can be taken to compute the ROI
for a data governance initiative: 1. Define all improper or incorrect
data governance activities
2. Define the total number of improper or incorrect activities as “A”
3. Define the cost per unit of this improper or incorrect data governance
activity in dollars as “B” 4. Identify the total number of units of the
improper or incorrect activity mentioned in (3) above as “C” 5. Compute
the projected savings by making corrections to this data governance
activity [as mentioned in 3 and 4 above] in dollars as “S”= (B * C) 6.
Compute the total savings by making corrections to all the improper or
incorrect data governance activities as T= Sigma of “Si”, where i= 1 to
A 7. Let the number of data governance roles involved in this effort be
“D”
8. Let the number of hours put by a particular data governance role be
“E”
9. Let the rate of the role in (8) above per hour be in dollars be “F”
10. Let the cost of the other resources needed for the data
governance initiative be “G”
11. Compute the cost of implementing these corrections as P = [Sigma
of (Ei * Fi), where i = 1 to D] + [ G ] 12. Finally let “R” be the ROI of the
above data governance led effort in dollars , where R = (T - P) 13. If R
> 0 and R >> P, then it is recommended to initiate the data governance
project, ELSE, 14. Revisit the estimates of the data
governance project such that R>0 and R>>A
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[ July,2007 Issue , Page 8 ]
